/*
 * Copyright (c) 2020-2021 Arm Limited.
 *
 * SPDX-License-Identifier: MIT
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to
 * deal in the Software without restriction, including without limitation the
 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
 * sell copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in all
 * copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 * SOFTWARE.
 */
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/ITensorPack.h"
#include "arm_compute/core/Window.h"
#include "src/core/NEON/NEMath.h"
#include "src/core/NEON/wrapper/wrapper.h"

#include <arm_neon.h>
#include <cmath>
#include <cstddef>

namespace arm_compute
{
namespace cpu
{
namespace
{
#ifndef __aarch64__
inline float32x4_t mask_float_vector(const float32x4_t &in, const uint32x4_t &mask)
{
    auto int_in = vreinterpretq_u32_f32(in);
    return vreinterpretq_f32_u32(wrapper::vand(int_in, mask));
}
#endif /* __aarch64__ */
} // namespace

void fp32_neon_activation(const ITensor *src, ITensor *dst, const ActivationLayerInfo &act_info, const Window &window)
{
    /** SIMD vector tag type. */
    using ExactTagType = typename arm_compute::wrapper::traits::neon_bitvector_tag_t<float, wrapper::traits::BitWidth::W128>;

    constexpr int                                 window_step_x  = 4;
    const auto                                    window_start_x = static_cast<int>(window.x().start());
    const auto                                    window_end_x   = static_cast<int>(window.x().end());
    const ActivationLayerInfo::ActivationFunction act            = act_info.activation();

    Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
    win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));

    Iterator input(src, win_collapsed);
    Iterator output(dst, win_collapsed);

    // In case of non-aarch64, a small delta value is added to the input
    // to prevent NAN values caused by zeros in inputs to SQRT.
    // In case of aarh64, we call vsqrt directly, so we don't use delta.
#ifndef __aarch64__
    const auto delta = wrapper::vdup_n(static_cast<float>(1e-24), ExactTagType {});
#endif /* __aarch64__ */
    const auto const_1     = wrapper::vdup_n(static_cast<float>(1.f), ExactTagType {});
    const auto const_0     = wrapper::vdup_n(static_cast<float>(0.f), ExactTagType{});
    const auto const_6     = wrapper::vdup_n(static_cast<float>(6.f), ExactTagType{});
    const auto const_3     = wrapper::vdup_n(static_cast<float>(3.f), ExactTagType{});
    const auto const_inv_6 = wrapper::vdup_n(static_cast<float>(0.166666667f), ExactTagType{});

    constexpr float soft_relu_thresh  = 12.f;
    const auto      vsoft_relu_thresh = wrapper::vdup_n(static_cast<float>(soft_relu_thresh), ExactTagType{});

    const auto va = wrapper::vdup_n(static_cast<float>(act_info.a()), ExactTagType{});
    const auto vb = wrapper::vdup_n(static_cast<float>(act_info.b()), ExactTagType{});
    const auto a  = static_cast<float>(act_info.a());
    const auto b  = static_cast<float>(act_info.b());
    execute_window_loop(win_collapsed, [&](const Coordinates &)
    {
        const auto input_ptr  = reinterpret_cast<const float *>(input.ptr());
        const auto output_ptr = reinterpret_cast<float *>(output.ptr());

        wrapper::traits::neon_bitvector_t<float, wrapper::traits::BitWidth::W128> tmp;

        // Compute S elements per iteration
        int x = window_start_x;
        for(; x <= (window_end_x - window_step_x); x += window_step_x)
        {
            const auto vin = wrapper::vloadq(input_ptr + x);
            switch(act)
            {
                case ActivationLayerInfo::ActivationFunction::ABS:
                    tmp = wrapper::vabs(vin);
                    break;
                case ActivationLayerInfo::ActivationFunction::LINEAR:
                    tmp = wrapper::vmla(vb, va, vin);
                    break;
                case ActivationLayerInfo::ActivationFunction::LOGISTIC:
                    tmp = wrapper::vinv(wrapper::vadd(const_1, wrapper::vexpq(wrapper::vneg(vin))));
                    break;
                case ActivationLayerInfo::ActivationFunction::RELU:
                    tmp = wrapper::vmax(const_0, vin);
                    break;
                case ActivationLayerInfo::ActivationFunction::BOUNDED_RELU:
                    tmp = wrapper::vmin(va, wrapper::vmax(const_0, vin));
                    break;
                case ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU:
                    tmp = wrapper::vmin(va, wrapper::vmax(vb, vin));
                    break;
                case ActivationLayerInfo::ActivationFunction::LEAKY_RELU:
                    tmp = wrapper::vbsl(wrapper::vcgt(vin, const_0), vin, wrapper::vmul(va, vin));
                    break;
                case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
                    tmp = wrapper::vbsl(wrapper::vcgt(vin, vsoft_relu_thresh), vin, wrapper::vlog(wrapper::vadd(const_1, wrapper::vexpq(vin))));
                    break;
                case ActivationLayerInfo::ActivationFunction::ELU:
                    tmp = wrapper::vbsl(wrapper::vcge(vin, const_0), vin, wrapper::vmul(va, wrapper::vsub(wrapper::vexpq(vin), const_1)));
                    break;
                case ActivationLayerInfo::ActivationFunction::SQRT:
#ifdef __aarch64__
                    tmp = wrapper::vsqrt(vin);
#else  /* __aarch64__ */
                    {
                        const auto bitmask = wrapper::vceq(vin, wrapper::vdup_n(0.f, ExactTagType{}));
                        tmp                 = wrapper::vinv(wrapper::vinvsqrt(wrapper::vadd(vin, mask_float_vector(delta, bitmask))));
                        tmp                 = mask_float_vector(tmp, wrapper::vnot(bitmask));
                    }
#endif /* __aarch64__ */
                    break;
                case ActivationLayerInfo::ActivationFunction::SQUARE:
                    tmp = wrapper::vmul(vin, vin);
                    break;
                case ActivationLayerInfo::ActivationFunction::TANH:
                    tmp = wrapper::vmul(va, wrapper::vtanh(wrapper::vmul(vb, vin)));
                    break;
                case ActivationLayerInfo::ActivationFunction::IDENTITY:
                    tmp = vin;
                    break;
                case ActivationLayerInfo::ActivationFunction::HARD_SWISH:
                    tmp = wrapper::vmul(vin, wrapper::vmul(const_inv_6, wrapper::vmin(const_6, wrapper::vmax(const_0, wrapper::vadd(vin, const_3)))));
                    break;
                default:
                    ARM_COMPUTE_ERROR("Unsupported activation function");
            }
            wrapper::vstore(output_ptr + x, tmp);
        }

        // Compute left-over elements
        for(; x < window_end_x; ++x)
        {
            const float in = *(reinterpret_cast<const float *>(input_ptr + x));
            float       tmp;
            switch(act)
            {
                case ActivationLayerInfo::ActivationFunction::ABS:
                    tmp = std::abs(in);
                    break;
                case ActivationLayerInfo::ActivationFunction::LINEAR:
                    tmp = a * in + b;
                    break;
                case ActivationLayerInfo::ActivationFunction::LOGISTIC:
                    tmp = static_cast<float>(1) / (static_cast<float>(1) + std::exp(-in));
                    break;
                case ActivationLayerInfo::ActivationFunction::RELU:
                    tmp = std::max<float>(static_cast<float>(0), in);
                    break;
                case ActivationLayerInfo::ActivationFunction::BOUNDED_RELU:
                    tmp = std::min<float>(a, std::max(static_cast<float>(0), in));
                    break;
                case ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU:
                    tmp = std::min<float>(a, std::max<float>(b, in));
                    break;
                case ActivationLayerInfo::ActivationFunction::LEAKY_RELU:
                    tmp = (in > 0) ? in : a * in;
                    break;
                case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
                    tmp = (in > soft_relu_thresh) ? in : std::log(static_cast<float>(1) + std::exp(in));
                    break;
                case ActivationLayerInfo::ActivationFunction::ELU:
                    tmp = (in >= 0) ? in : a * (std::exp(in) - 1);
                    break;
                case ActivationLayerInfo::ActivationFunction::SQRT:
                    tmp = std::sqrt(in);
                    break;
                case ActivationLayerInfo::ActivationFunction::SQUARE:
                    tmp = in * in;
                    break;
                case ActivationLayerInfo::ActivationFunction::TANH:
                    tmp = a * std::tanh(b * in);
                    break;
                case ActivationLayerInfo::ActivationFunction::IDENTITY:
                    tmp = in;
                    break;
                case ActivationLayerInfo::ActivationFunction::HARD_SWISH:
                    tmp = in * ((std::min(std::max((in + 3), 0.0f), 6.0f)) * 0.166666667f);
                    break;
                default:
                    ARM_COMPUTE_ERROR("Unsupported activation function");
            }
            *(output_ptr + x) = tmp;
        }
    },
    input, output);
}
} // namespace cpu
} // namespace arm_compute
